References

Balın, Muhammed Fatih, Abubakar Abid, and James Zou. 2019. “Concrete Autoencoders: Differentiable Feature Selection and Reconstruction.” In International Conference on Machine Learning, 444–53. PMLR.

Bao, Shunxing, Yucheng Tang, Ho Hin Lee, Riqiang Gao, Sophie Chiron, Ilwoo Lyu, Lori A Coburn, et al. 2021. “Random Multi-Channel Image Synthesis for Multiplexed Immunofluorescence Imaging.” In MICCAI Workshop on Computational Pathology, 36–46. PMLR.

Bok, Vladimir, and Jakub Langr. 2019. GANs in Action: Deep Learning with Generative Adversarial Networks. Simon; Schuster.

Chen, Bob, Scurrah Cherie’R, Eliot T McKinley, Alan J Simmons, Marisol A Ramirez-Solano, Xiangzhu Zhu, Nicholas O Markham, et al. 2021. “Differential Pre-Malignant Programs and Microenvironment Chart Distinct Paths to Malignancy in Human Colorectal Polyps.” Cell 184 (26): 6262–80.

Chen, Tianqi, and Carlos Guestrin. 2016. “Xgboost: A Scalable Tree Boosting System.” In Proceedings of the 22nd Acm Sigkdd International Conference on Knowledge Discovery and Data Mining, 785–94.

Coons, Albert H, Hugh J Creech, and R Norman Jones. 1941. “Immunological Properties of an Antibody Containing a Fluorescent Group.” Proceedings of the Society for Experimental Biology and Medicine 47 (2): 200–202.

Duraiyan, Jeyapradha, Rajeshwar Govindarajan, Karunakaran Kaliyappan, and Murugesan Palanisamy. 2012. “Applications of Immunohistochemistry.” Journal of Pharmacy & Bioallied Sciences 4 (Suppl 2): S307.

Eng, Jennifer, Elmar Bucher, Zhi Hu, Ting Zheng, Summer L Gibbs, Koei Chin, and Joe W Gray. 2022. “A Framework for Multiplex Imaging Optimization and Reproducible Analysis.” Communications Biology 5 (1): 438.

Goodfellow, Ian, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio. 2014. “Generative Adversarial Nets.” Advances in Neural Information Processing Systems 27.

Hussaini, Haizal Mohd, Benedict Seo, and Alison M Rich. 2022. “Immunohistochemistry and Immunofluorescence.” In Oral Biology: Molecular Techniques and Applications, 439–50. Springer.

Isola, Phillip, Jun-Yan Zhu, Tinghui Zhou, and Alexei A Efros. 2017. “Image-to-Image Translation with Conditional Adversarial Networks.” In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 1125–34.

McKinley, Eliot T, Justin Shao, Samuel T Ellis, Cody N Heiser, Joseph T Roland, Mary C Macedonia, Paige N Vega, Susie Shin, Robert J Coffey, and Ken S Lau. 2022. “MIRIAM: A Machine and Deep Learning Single-Cell Segmentation and Quantification Pipeline for Multi-Dimensional Tissue Images.” Cytometry Part A 101 (6): 521–28.

Mirza, Mehdi, and Simon Osindero. 2014. “Conditional Generative Adversarial Nets.” arXiv Preprint arXiv:1411.1784.

Ramos-Vara, Jose A. 2005. “Technical Aspects of Immunohistochemistry.” Veterinary Pathology 42 (4): 405–26.

Rubin, Donald B. 1996. “Multiple Imputation After 18+ Years.” Journal of the American Statistical Association 91 (434): 473–89.

Schüffler, Peter J, Denis Schapiro, Charlotte Giesen, Hao AO Wang, Bernd Bodenmiller, and Joachim M Buhmann. 2015. “Automatic Single Cell Segmentation on Highly Multiplexed Tissue Images.” Cytometry Part A 87 (10): 936–42.

Schürch, Christian M, Salil S Bhate, Graham L Barlow, Darci J Phillips, Luca Noti, Inti Zlobec, Pauline Chu, et al. 2020. “Coordinated Cellular Neighborhoods Orchestrate Antitumoral Immunity at the Colorectal Cancer Invasive Front.” Cell 182 (5): 1341–59.

Sheng, Wenjie, Chaoyu Zhang, TM Mohiuddin, Marwah Al-Rawe, Felix Zeppernick, Franco H Falcone, Ivo Meinhold-Heerlein, and Ahmad Fawzi Hussain. 2023. “Multiplex Immunofluorescence: A Powerful Tool in Cancer Immunotherapy.” International Journal of Molecular Sciences 24 (4): 3086.

Sims, Zachary, and Young Hwan Chang. 2023. “A Masked Image Modeling Approach to Cyclic Immunofluorescence (CyCIF) Panel Reduction and Marker Imputation.” bioRxiv, 2023–05.

Souza, Vinicius Luis Trevisan de, Bruno Augusto Dorta Marques, Harlen Costa Batagelo, and João Paulo Gois. 2023. “A Review on Generative Adversarial Networks for Image Generation.” Computers & Graphics.

Steinhart, Benjamin, Kimberly R Jordan, Jaidev Bapat, Miriam D Post, Lindsay W Brubaker, Benjamin G Bitler, and Julia Wrobel. 2021. “The Spatial Context of Tumor-Infiltrating Immune Cells Associates with Improved Ovarian Cancer Survival.” Molecular Cancer Research 19 (12): 1973–79.

Ternes, Luke, Jia-Ren Lin, Yu-An Chen, Joe W Gray, and Young Hwan Chang. 2022. “Computational Multiplex Panel Reduction to Maximize Information Retention in Breast Cancer Tissue Microarrays.” PLoS Computational Biology 18 (9): e1010505.

Van Buuren, Stef. 2018. Flexible Imputation of Missing Data. CRC press.

Wang, Zhou, A. C. Bovik, H. R. Sheikh, and E. P. Simoncelli. 2004. “Image Quality Assessment: From Error Visibility to Structural Similarity.” IEEE Transactions on Image Processing 13 (4): 600–612. https://doi.org/10.1109/TIP.2003.819861.

Wrobel, Julia, Coleman Harris, and Simon Vandekar. 2023. “Statistical Analysis of Multiplex Immunofluorescence and Immunohistochemistry Imaging Data.” In Statistical Genomics, 141–68. Springer.

Wu, Eric, Alexandro E Trevino, Zhenqin Wu, Kyle Swanson, Honesty J Kim, H Blaize D’Angio, Ryan Preska, et al. 2023. “7-UP: Generating in Silico CODEX from a Small Set of Immunofluorescence Markers.” PNAS Nexus 2 (6): pgad171.